Conventionally, the computed radiography (CR) can only be processed in a manner of batch operation. For example, a batch operation can process 60 x-ray films per hour. Though the batch operation might reduce cost, yet a necessary step of scanning the x-ray films through a CR reader to generate corresponding digital signals before the batch images can be processed in a computer system is cumbersome. Recently, a new technology (Digital radiography, DR) has been introduced to obtain digitized images directly by waiving the scanning process of the CR reader. Certainly, this DR technique has been the mainstream of the x-ray imaging equipment. In particular, a novel digital x-ray tomosynthesis that is capable of synthesizing multi-angle x-ray images into a three-dimensional image has substantially resolved the realization defects upon the disease or specific tissue on a conventional digital x-ray image. Further, for imaging by this tomosynthesis does not require whole-angle image-capturing, this the imaging time can be greatly reduced. Also, radiation doses taken by the involved personals in this novel tomosynthesis are proved to be less than those in the conventional CT.
Generally, image reconstruction techniques can be classified into direct methods and iterative methods. In the past, various direct methods have been vastly used to reconstruct rapidly the images, definitely by sacrificing the resolutions. For example, in the GE Discovery XR656, a digital CT, the volume-RAD MITS (Magnetic imaging technology scan) developed by Duke University is applied; and, in the Shimadzu SONIALVISION safire series, the universal x-ray imaging device applies the conventional shift-and-add technique or the FBP technique. Recently, some iterative methods such as the ART, MLEM and son on, are also applied to the tomosynthesis.
Typically, in an iterative method, provided that a vector P(M×1) is defined to be the received signal stored in the computer in a discrete array manner, its dimension would be the product of the sensor number and the film number. A mathematical model for image reconstruction of the tomosynthesis can be formulated discretely as GF=p, in which the G(M×N) stands for a system array and the F(N×1) stands for the desired 3D image. Since photos travel linearly in the space, and provided that the signal in the imaging device is emitted by a light source with a specific volume and received by a specific sensor, then, without considering light scattering and other physical factors, the G can be simplified to be a matrix formulating geometric relationship. The entry gij of matrix G stands for the geometric detecting effect of the i-th voxel with respect to the j-th sensor. To different sensors at different positions, the signal-receiving outcomes would be different. These signal-receiving outcomes shall be fed back to the reconstruction computation so as to modify the spatial distribution.
Generally, the imaging theory of the tomosynthesis and that of the CT are similar. However, sampling in a tomosynthesis procession is limited to a specific angular range, from which incomplete G and P information would be inevitable. Further, the cutting direction for reconstructing images of this tomosynthesis is different to that of CT. Thereupon, artifacts that might affect the following image reading would be formed during the image-reconstruction process. For example, a ripple artifact would be caused by an insufficient scanning density, a ghost artifact would be caused by an irrelevant scanning direction, and a metallic artifact would be caused from scanning an object with a metallic matter. Unlike the 360-degree whole-angle CT that can provide sufficient scanning samples, in order to lower the radiological dose by cutting down the scanning or projection samples, truncation errors during the image reconstruction would be quite possible to occur at the boundary of the sensor. Namely, a small sampling frequency would lead to the phenomenon of boundary artifacts on the resulted 3D image. If any artifact falls at the major part to be investigated (for example, a shoulder blade in a chest scan), then the clinical diagnosis thereupon would be substantially affected.
Hence, the issue how to reduce the occurrence of the boundary artifacts on the tomosynthesis is definitely crucial in the art.